Modern Earth and environmental scientists deal with complex and often very large
quantitative datasets that are typically not useful or understandable in raw form. Thus,
quantitative data analysis skills are highly desired and useful in quantitative Earth science
subdisciplines. This course provides an introduction to processing, visualizing, and
interpreting quantitative Earth and environmental science data using scientific computing
techniques widely used in the Earth sciences. Computational methods and visualization
will be performed using the scientific computing language, MATLAB. Previous
programming experience is not required. Weekly meetings introduce the necessary
theoretical and computational background to complete weekly assignments that
demonstrate applications to Earth science data. The weekly assignments will involve
writing algorithms that use quantitative methods to process and visualize data relevant to
the Earth sciences. Expected topics to be covered may include Earth science applications
of: conditional statements, loops, vector and matrix operations, importing data, automated
data analysis & visualization (including 3D visualization), differentiation, interpolation,
filtering, curve fitting, error estimation and propagation, and linear regression and
confidence interval estimation.
- Kursleiter/in: Rebecca Maria Harrington